Financial exchanges across the world use limit order books (LOBs) to pro...
Accurate 3D cardiac reconstruction from cine magnetic resonance imaging
...
It is necessary to analyze the whole-body kinematics (including joint
lo...
Pretraining with large-scale 3D volumes has a potential for improving th...
Karyotyping is of importance for detecting chromosomal aberrations in hu...
Masked autoencoder (MAE) has attracted unprecedented attention and achie...
Large pre-trained vision-language models have shown great prominence in
...
The Segment Anything Model (SAM) made an eye-catching debut recently and...
Adversarial training and data augmentation with noise are widely adopted...
The information diffusion performance of GCN and its variant models is
l...
Inevitable domain and task discrepancies in real-world scenarios can imp...
In this paper, we propose an effective sound event detection (SED) metho...
Generalization to previously unseen images with potential domain shifts ...
Contemporary methods have shown promising results on cardiac image
segme...
The large-scale pre-trained vision language models (VLM) have shown
rema...
Background and Objective: Existing deep learning platforms for medical i...
The success of Convolutional Neural Networks (CNNs) in 3D medical image
...
Monocular image-based 3D perception has become an active research area i...
Accurate segmentation of Anatomical brain Barriers to Cancer spread (ABC...
For diagnosis of shoulder illness, it is essential to look at the morpho...
The repairing work of terracotta warriors in Emperor Qinshihuang Mausole...
Simulation-based virtual testing has become an essential step to ensure ...
Automatic and accurate lung nodule detection from 3D Computed Tomography...
Rowhammer attacks that corrupt level-1 page tables to gain kernel privil...
Deep neural networks (DNNs) have been applied in a wide range of
applica...
We consider the problem of explaining the predictions of graph neural
ne...
Annotation scarcity is a long-standing problem in medical image analysis...
In this paper, we present a seed-region-growing CNN(SRG-Net) for unsuper...
Deep convolutional neural networks have significantly boosted the perfor...
NLP models are shown to suffer from robustness issues, i.e., a model's
p...
The success of deep convolutional neural networks is partially attribute...
Medical image annotations are prohibitively time-consuming and expensive...
Nuclei segmentation is a fundamental task in histopathology image analys...
The 3D morphology and quantitative assessment of knee articular cartilag...
Accurate segmentation of the optic disc (OD) and cup (OC)in fundus image...
The aim of this study is developing an automatic system for detection of...
For the initial shoulder preoperative diagnosis, it is essential to obta...
Lifting is a common manual material handling task performed in the
workp...
This paper describes the development of a real-time Human-Robot Interact...
Surveillance is essential for the safety of power substation. The detect...
This paper considers security risks buried in the data processing pipeli...
Advance in deep learning algorithms overshadows their security risk in
s...
For the problem whether Graphic Processing Unit(GPU),the stream processo...